You are not currently logged in.
Access JSTOR through your library or other institution:
On the Elimination of Nuisance Parameters
Journal of the American Statistical Association
Vol. 72, No. 358 (Jun., 1977), pp. 355-366
Stable URL: http://www.jstor.org/stable/2286800
Page Count: 12
You can always find the topics here!Topics: Statistics, Statistical models, Mathematical independent variables, Mathematical functions, Factorization, Marginalization, Mathematical problems, Probabilities, Statistical theories, Statistical relevance model
Were these topics helpful?See somethings inaccurate? Let us know!
Select the topics that are inaccurate.
Preview not available
Eliminating nuisance parameters from a model is universally recognized as a major problem of statistics. A surprisingly large number of elimination methods have been proposed by various writers on the topic. In this article we propose to critically review two such elimination methods. We shall be concerned with some particular cases of the marginalizing and the conditioning methods. The origin of these methods may be traced to the work of Sir Ronald A. Fisher. The contents of the marginalization and the conditionality arguments are then reexamined from the Bayesian point of view. This article should be regarded as a sequel to the author's three-part essay (Basu 1975) on statistical information and likelihood.
Journal of the American Statistical Association © 1977 American Statistical Association